Multidimensional Assessment and Distributional Characteristics of Low-wind-power Events in High Proportion Renewable Energy Power Systems

In power systems with a high penetration of renewable energy, large-scale calm and low wind speeds that lead to wind power output significantly falling below expectations result in Low-Wind-Power (LWP) events, posing significant challenges to the power balance of the system. Due to the relatively short period of high wind power penetration, historical data records have not yet encompassed various complex meteorological scenarios, making it difficult to gain an in-depth understanding of LWP events. This paper proposes a low wind power event assessment method based on meteorological data inversion, analyzing the interannual, intra-annual, and extreme value distributions of these events from multiple dimensions, such as low output intensity and duration. The method first utilizes reanalysis meteorological data from 1979 to 2023 to invert hourly regional historical wind power output sequences. Then, a moving average detection method is applied to identify LWP events and analyze their interannual and intra-annual statistical distribution characteristics as well as long-term trends. Finally, a "return period" indicator is proposed to quantify the recurrence interval of LWP events. The research provides support for flexibility planning in power systems with high renewable energy penetration.